{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}\\file\UsersW$\wrr15\Home\My Documents\My Files\FIGO'S PAPER\REVISION FOR ECONOMICS E-JOURNAL\Revision (20180407)\FILES FROM FIGO (20180420)\MainResults.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res}20 Apr 2018, 09:10:10
{txt}
{com}. 
. etime, start
{txt}
{com}. 
. use "\\file\UsersW$\wrr15\Home\My Documents\My Files\FIGO'S PAPER\REVISION FOR ECONOMICS E-JOURNAL\Revision (20180407)\FILES FROM FIGO (20180420)\FullSample1998-2011.dta"
{txt}
{com}. 
. rename YEAR year
{res}{txt}
{com}. 
. keep if ASSETS>0 
{txt}(0 observations deleted)

{com}. keep if PROFITS>0
{txt}(0 observations deleted)

{com}. keep if EMP>8
{txt}(0 observations deleted)

{com}. drop if DEBT<0  
{txt}(0 observations deleted)

{com}. 
. // We need to delete the fake MNCs by using the following two criteria
. 
. keep if FOREIGNCAPITAL > 0
{txt}(19,083 observations deleted)

{com}. gen ratio = FOREIGNCAPITAL/TOTALCAPITAL
{txt}(40,241 missing values generated)

{com}. keep if ratio > 0.25
{txt}(9,873 observations deleted)

{com}. 
. gen d=substr(regst_type,1,1)
{txt}
{com}. 
. count if d=="1"| d=="2"
  {res}0
{txt}
{com}. drop if d=="1" | d=="2" 
{txt}(0 observations deleted)

{com}. // 1 means the state-owned and private enterprise of China. 2 means the enterprises 
. // invested by HMT(Hong Kong, Macao, and Taiwan). 3 means the enterprise invested by foreign economies except HMT.
. 
. keep if d == "3"
{txt}(54 observations deleted)

{com}. 
. // We use ETR
. keep if ETR<100
{txt}(0 observations deleted)

{com}. keep if ETR>0
{txt}(0 observations deleted)

{com}. 
. // If we want, we can redo the analysis by dropping all observations where ETR > 33 percent.
. // drop if ETR > 33
. 
. 
. // This creates year dummies
. tabulate year, gen(year)

       {txt}year {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
       1998 {c |}{res}      2,218        1.57        1.57
{txt}       1999 {c |}{res}      2,647        1.88        3.45
{txt}       2000 {c |}{res}      3,192        2.26        5.71
{txt}       2001 {c |}{res}      3,771        2.67        8.38
{txt}       2002 {c |}{res}      4,555        3.23       11.61
{txt}       2003 {c |}{res}      5,552        3.93       15.54
{txt}       2004 {c |}{res}      9,088        6.44       21.98
{txt}       2005 {c |}{res}      9,779        6.93       28.91
{txt}       2006 {c |}{res}     11,670        8.27       37.17
{txt}       2007 {c |}{res}     13,152        9.32       46.49
{txt}       2008 {c |}{res}     14,820       10.50       56.99
{txt}       2009 {c |}{res}     20,855       14.77       71.76
{txt}       2010 {c |}{res}     19,034       13.48       85.25
{txt}       2011 {c |}{res}     20,825       14.75      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}    141,158      100.00
{txt}
{com}. // To make the output easier to read, we rename the year dummies
. rename year14  y2011
{res}{txt}
{com}. rename year13  y2010
{res}{txt}
{com}. rename year12  y2009
{res}{txt}
{com}. rename year11  y2008
{res}{txt}
{com}. rename year10  y2007
{res}{txt}
{com}. rename year9  y2006
{res}{txt}
{com}. rename year8  y2005
{res}{txt}
{com}. rename year7  y2004
{res}{txt}
{com}. rename year6  y2003
{res}{txt}
{com}. rename year5  y2002
{res}{txt}
{com}. rename year4  y2001
{res}{txt}
{com}. rename year3  y2000
{res}{txt}
{com}. rename year2  y1999
{res}{txt}
{com}. rename year1  y1998
{res}{txt}
{com}. 
. // This section produces the results for TABLE 2
. 
. // We run this regression to show the change in ETR over the different years of the sample
. reg ETR y1998-y2011, noconstant vce(cluster FIRM_id)

{txt}Linear regression                               Number of obs     = {res}   129,626
                                                {txt}F(14, 44301)      =  {res} 10073.94
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.6615
                                                {txt}Root MSE          =    {res} 12.068

{txt}{ralign 78:(Std. Err. adjusted for {res:44,302} clusters in FIRM_id)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}         ETR{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}y1998 {c |}{col 14}{res}{space 2} 17.50132{col 26}{space 2} .2495801{col 37}{space 1}   70.12{col 46}{space 3}0.000{col 54}{space 4} 17.01214{col 67}{space 3}  17.9905
{txt}{space 7}y1999 {c |}{col 14}{res}{space 2}   16.826{col 26}{space 2} .2217475{col 37}{space 1}   75.88{col 46}{space 3}0.000{col 54}{space 4} 16.39137{col 67}{space 3} 17.26063
{txt}{space 7}y2000 {c |}{col 14}{res}{space 2} 16.78775{col 26}{space 2} .1972943{col 37}{space 1}   85.09{col 46}{space 3}0.000{col 54}{space 4} 16.40105{col 67}{space 3} 17.17445
{txt}{space 7}y2001 {c |}{col 14}{res}{space 2}  16.9688{col 26}{space 2}  .180286{col 37}{space 1}   94.12{col 46}{space 3}0.000{col 54}{space 4} 16.61544{col 67}{space 3} 17.32216
{txt}{space 7}y2002 {c |}{col 14}{res}{space 2} 17.21583{col 26}{space 2} .1743007{col 37}{space 1}   98.77{col 46}{space 3}0.000{col 54}{space 4}  16.8742{col 67}{space 3} 17.55746
{txt}{space 7}y2003 {c |}{col 14}{res}{space 2}  17.4522{col 26}{space 2} .1619979{col 37}{space 1}  107.73{col 46}{space 3}0.000{col 54}{space 4} 17.13468{col 67}{space 3} 17.76971
{txt}{space 7}y2004 {c |}{col 14}{res}{space 2} 17.60009{col 26}{space 2} .1298926{col 37}{space 1}  135.50{col 46}{space 3}0.000{col 54}{space 4}  17.3455{col 67}{space 3} 17.85468
{txt}{space 7}y2005 {c |}{col 14}{res}{space 2} 17.93407{col 26}{space 2} .1295159{col 37}{space 1}  138.47{col 46}{space 3}0.000{col 54}{space 4} 17.68021{col 67}{space 3} 18.18792
{txt}{space 7}y2006 {c |}{col 14}{res}{space 2} 17.77398{col 26}{space 2} .1168742{col 37}{space 1}  152.08{col 46}{space 3}0.000{col 54}{space 4} 17.54491{col 67}{space 3} 18.00306
{txt}{space 7}y2007 {c |}{col 14}{res}{space 2} 17.67832{col 26}{space 2} .1130706{col 37}{space 1}  156.35{col 46}{space 3}0.000{col 54}{space 4} 17.45669{col 67}{space 3} 17.89994
{txt}{space 7}y2008 {c |}{col 14}{res}{space 2} 18.39423{col 26}{space 2} .1022951{col 37}{space 1}  179.82{col 46}{space 3}0.000{col 54}{space 4} 18.19373{col 67}{space 3} 18.59473
{txt}{space 7}y2009 {c |}{col 14}{res}{space 2} 19.23161{col 26}{space 2} .1050906{col 37}{space 1}  183.00{col 46}{space 3}0.000{col 54}{space 4} 19.02563{col 67}{space 3} 19.43759
{txt}{space 7}y2010 {c |}{col 14}{res}{space 2} 12.75299{col 26}{space 2} .0950707{col 37}{space 1}  134.14{col 46}{space 3}0.000{col 54}{space 4} 12.56665{col 67}{space 3} 12.93933
{txt}{space 7}y2011 {c |}{col 14}{res}{space 2} 13.98091{col 26}{space 2}  .076265{col 37}{space 1}  183.32{col 46}{space 3}0.000{col 54}{space 4} 13.83143{col 67}{space 3} 14.13039
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. gen insamplea = e(sample)
{txt}
{com}. tabulate year if insamplea == 1

       {txt}year {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
       1998 {c |}{res}      2,218        1.71        1.71
{txt}       1999 {c |}{res}      2,647        2.04        3.75
{txt}       2000 {c |}{res}      3,192        2.46        6.22
{txt}       2001 {c |}{res}      3,771        2.91        9.12
{txt}       2002 {c |}{res}      4,555        3.51       12.64
{txt}       2003 {c |}{res}      5,552        4.28       16.92
{txt}       2004 {c |}{res}      9,088        7.01       23.93
{txt}       2005 {c |}{res}      9,779        7.54       31.48
{txt}       2006 {c |}{res}     11,670        9.00       40.48
{txt}       2007 {c |}{res}     13,152       10.15       50.63
{txt}       2008 {c |}{res}     14,820       11.43       62.06
{txt}       2009 {c |}{res}     14,401       11.11       73.17
{txt}       2010 {c |}{res}     13,956       10.77       83.93
{txt}       2011 {c |}{res}     20,825       16.07      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}    129,626      100.00
{txt}
{com}. // There is a substantial drop in ETR in years 13 and 14 (2010 and 2011),so we drop these years. 
. // This still gives us two, post-law change years (years 11 and 12 = 2008 and 2009)
. // The subsequent analysis focuses on the years before 2010.
. 
. // This sets the sample we will work on in the subsequent analysis
. quietly reg lnPROFITS ETR lnSALES lnEMP lnGDP lnKLRAT lnSKILL lnLABOR lnMARK ///
> lnPOPDEN lnINFRAS lnFINANCE lnINVFOR y2005-y2009 if year < 2010, vce(cluster FIRM_id)
{txt}
{com}. gen insample = e(sample)
{txt}
{com}. 
. // This show us the degree of foreign ownership of the MNCs in our sample
. . histogram FOREIGN if insample == 1, percent
{txt}(bin={res}46{txt}, start={res}.25000015{txt}, width={res}.06029412{txt})
{res}{txt}
{com}. 
. // This lets us know how many observations we have per year
. tabulate year if insample == 1

       {txt}year {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
       2005 {c |}{res}      9,637       16.67       16.67
{txt}       2006 {c |}{res}     11,400       19.72       36.39
{txt}       2007 {c |}{res}     13,098       22.66       59.06
{txt}       2008 {c |}{res}     11,294       19.54       78.59
{txt}       2009 {c |}{res}     12,373       21.41      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}     57,802      100.00
{txt}
{com}. // We see that we only have observations from 2005-2009
. 
. // This produces the histogram for FIGURE 1
. histogram ETR, percent
{txt}(bin={res}51{txt}, start={res}.00002625{txt}, width={res}1.9606447{txt})
{res}{txt}
{com}. 
. // This produces the descriptive statistics reported in TABLE 3
. summ PROFITS ASSETS ETR SALES EMP GDP KLRAT SKILL LABOR MARK POPDEN INFRAS ///
>      FINANCE INVFOR y2005 y2006 y2007 y2008 y2009 if insample == 1

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 5}PROFITS {c |}{res}     57,802    25455.13    160239.7          2   1.47e+07
{txt}{space 6}ASSETS {c |}{res}     57,799    68771.15      417674          1   2.53e+07
{txt}{space 9}ETR {c |}{res}     57,802    18.26061    12.71835   .0000262    99.9929
{txt}{space 7}SALES {c |}{res}     57,802    326978.8     2389984         41   1.92e+08
{txt}{space 9}EMP {c |}{res}     57,802    423.5405    1798.512          9     198971
{txt}{hline 13}{c +}{hline 57}
{space 9}GDP {c |}{res}     57,802    4.54e+07    3.85e+07     981093   1.50e+08
{txt}{space 7}KLRAT {c |}{res}     57,802    193.0383    1020.567   .0002476   91083.86
{txt}{space 7}SKILL {c |}{res}     57,802    286.2006     204.536   4.321882   1228.058
{txt}{space 7}LABOR {c |}{res}     57,802    32741.35    11410.27    6409.73   118685.3
{txt}{space 8}MARK {c |}{res}     57,802    .1071196     .044232   .0426538   1.936383
{txt}{hline 13}{c +}{hline 57}
{space 6}POPDEN {c |}{res}     57,802    .0885465    .0567083     .00047   .2661542
{txt}{space 6}INFRAS {c |}{res}     57,802    .0117182    .0123184   .0004021   .0561067
{txt}{space 5}FINANCE {c |}{res}     57,802    .0075167    .0060729   .0006482   .0361731
{txt}{space 6}INVFOR {c |}{res}     57,802    330853.9    295131.4         22    1053835
{txt}{space 7}y2005 {c |}{res}     57,802    .1667243    .3727328          0          1
{txt}{hline 13}{c +}{hline 57}
{space 7}y2006 {c |}{res}     57,802     .197225    .3979071          0          1
{txt}{space 7}y2007 {c |}{res}     57,802    .2266012     .418636          0          1
{txt}{space 7}y2008 {c |}{res}     57,802    .1953912     .396505          0          1
{txt}{space 7}y2009 {c |}{res}     57,802    .2140583     .410171          0          1
{txt}
{com}. 
. ***********************
. ***********************
. ******           ******
. ******  PROFITS  ******
. ******           ******
. ***********************
. ***********************
. 
. // This section produces the results for TABLE 4
. 
. // Basic equation for PROFIT regression
. // This regression shows a significant, negative relationship between ETR and PROFITS. Ceteris paribus, 
. // higher ETR is associated with lower profits, consistent with profit-shifting
. 
. reg lnPROFITS ETR if insample == 1, vce(cluster FIRM_id)

{txt}Linear regression                               Number of obs     = {res}    57,802
                                                {txt}F(1, 28043)       =  {res}  2601.65
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0568
                                                {txt}Root MSE          =    {res} 1.9737

{txt}{ralign 78:(Std. Err. adjusted for {res:28,044} clusters in FIRM_id)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}   lnPROFITS{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}ETR {c |}{col 14}{res}{space 2} -.038085{col 26}{space 2} .0007467{col 37}{space 1}  -51.01{col 46}{space 3}0.000{col 54}{space 4}-.0395486{col 67}{space 3}-.0366215
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 8.755317{col 26}{space 2} .0188688{col 37}{space 1}  464.01{col 46}{space 3}0.000{col 54}{space 4} 8.718333{col 67}{space 3}   8.7923
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. reg lnPROFITS ETR lnSALES lnEMP lnGDP lnKLRAT lnSKILL lnLABOR lnMARK lnPOPDEN ///
>     lnINFRAS lnFINANCE lnINVFOR y2006-y2009 if insample == 1, vce(cluster FIRM_id)

{txt}Linear regression                               Number of obs     = {res}    57,802
                                                {txt}F(16, 28043)      =  {res}  3622.47
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.6599
                                                {txt}Root MSE          =    {res} 1.1853

{txt}{ralign 78:(Std. Err. adjusted for {res:28,044} clusters in FIRM_id)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}   lnPROFITS{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}ETR {c |}{col 14}{res}{space 2}-.0237455{col 26}{space 2} .0004769{col 37}{space 1}  -49.79{col 46}{space 3}0.000{col 54}{space 4}-.0246803{col 67}{space 3}-.0228107
{txt}{space 5}lnSALES {c |}{col 14}{res}{space 2} 1.039828{col 26}{space 2}  .008023{col 37}{space 1}  129.61{col 46}{space 3}0.000{col 54}{space 4} 1.024103{col 67}{space 3} 1.055554
{txt}{space 7}lnEMP {c |}{col 14}{res}{space 2}-.0136711{col 26}{space 2}  .009573{col 37}{space 1}   -1.43{col 46}{space 3}0.153{col 54}{space 4}-.0324346{col 67}{space 3} .0050924
{txt}{space 7}lnGDP {c |}{col 14}{res}{space 2} .2136786{col 26}{space 2} .0207232{col 37}{space 1}   10.31{col 46}{space 3}0.000{col 54}{space 4} .1730602{col 67}{space 3} .2542971
{txt}{space 5}lnKLRAT {c |}{col 14}{res}{space 2} .1298332{col 26}{space 2} .0057664{col 37}{space 1}   22.52{col 46}{space 3}0.000{col 54}{space 4} .1185306{col 67}{space 3} .1411357
{txt}{space 5}lnSKILL {c |}{col 14}{res}{space 2} .0801903{col 26}{space 2} .0148352{col 37}{space 1}    5.41{col 46}{space 3}0.000{col 54}{space 4} .0511127{col 67}{space 3}  .109268
{txt}{space 5}lnLABOR {c |}{col 14}{res}{space 2}-.2718343{col 26}{space 2}  .054462{col 37}{space 1}   -4.99{col 46}{space 3}0.000{col 54}{space 4}-.3785825{col 67}{space 3}-.1650861
{txt}{space 6}lnMARK {c |}{col 14}{res}{space 2} .3275567{col 26}{space 2} .0273069{col 37}{space 1}   12.00{col 46}{space 3}0.000{col 54}{space 4} .2740338{col 67}{space 3} .3810796
{txt}{space 4}lnPOPDEN {c |}{col 14}{res}{space 2}-.0129678{col 26}{space 2} .0175966{col 37}{space 1}   -0.74{col 46}{space 3}0.461{col 54}{space 4} -.047458{col 67}{space 3} .0215224
{txt}{space 4}lnINFRAS {c |}{col 14}{res}{space 2}  .023646{col 26}{space 2} .0210298{col 37}{space 1}    1.12{col 46}{space 3}0.261{col 54}{space 4}-.0175735{col 67}{space 3} .0648654
{txt}{space 3}lnFINANCE {c |}{col 14}{res}{space 2}-.2560118{col 26}{space 2} .0258792{col 37}{space 1}   -9.89{col 46}{space 3}0.000{col 54}{space 4}-.3067362{col 67}{space 3}-.2052873
{txt}{space 4}lnINVFOR {c |}{col 14}{res}{space 2}-.0300588{col 26}{space 2} .0112396{col 37}{space 1}   -2.67{col 46}{space 3}0.007{col 54}{space 4} -.052089{col 67}{space 3}-.0080286
{txt}{space 7}y2006 {c |}{col 14}{res}{space 2}-.0027963{col 26}{space 2}  .013759{col 37}{space 1}   -0.20{col 46}{space 3}0.839{col 54}{space 4}-.0297646{col 67}{space 3} .0241721
{txt}{space 7}y2007 {c |}{col 14}{res}{space 2}-.0063538{col 26}{space 2} .0201047{col 37}{space 1}   -0.32{col 46}{space 3}0.752{col 54}{space 4}-.0457599{col 67}{space 3} .0330524
{txt}{space 7}y2008 {c |}{col 14}{res}{space 2}-.0408431{col 26}{space 2}  .024319{col 37}{space 1}   -1.68{col 46}{space 3}0.093{col 54}{space 4}-.0885095{col 67}{space 3} .0068233
{txt}{space 7}y2009 {c |}{col 14}{res}{space 2}-.0247234{col 26}{space 2}  .028419{col 37}{space 1}   -0.87{col 46}{space 3}0.384{col 54}{space 4} -.080426{col 67}{space 3} .0309792
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-4.934064{col 26}{space 2} .6043721{col 37}{space 1}   -8.16{col 46}{space 3}0.000{col 54}{space 4}-6.118663{col 67}{space 3}-3.749465
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. nbreg PROFITS ETR if insample == 1, dispersion(constant) vce(cluster FIRM_id)

{txt}Fitting Poisson model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-2.963e+09}  
Iteration 1:{space 3}log pseudolikelihood = {res:-2.963e+09}  
Iteration 2:{space 3}log pseudolikelihood = {res:-2.963e+09}  
{res}
{txt}Fitting constant-only model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-1.025e+09}  
Iteration 1:{space 3}log pseudolikelihood = {res:-664012.76}  
Iteration 2:{space 3}log pseudolikelihood = {res:-603707.51}  
Iteration 3:{space 3}log pseudolikelihood = {res: -603445.4}  
Iteration 4:{space 3}log pseudolikelihood = {res:-603444.81}  
Iteration 5:{space 3}log pseudolikelihood = {res:-603444.81}  
{res}
{txt}Fitting full model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-603444.81}  
Iteration 1:{space 3}log pseudolikelihood = {res:-602856.81}  
Iteration 2:{space 3}log pseudolikelihood = {res: -602852.3}  
Iteration 3:{space 3}log pseudolikelihood = {res: -602852.3}  
{res}
{txt}Negative binomial regression{col 49}Number of obs{col 67}= {res}    57,802
{txt}{col 49}Wald chi2({res}1{txt}){col 67}= {res}   1920.03
{txt}{col 1}Dispersion{col 22}= {res}constant{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log pseudolikelihood = {res} -602852.3{txt}{col 49}Pseudo R2{col 67}= {res}    0.0010

{txt}{ralign 78:(Std. Err. adjusted for {res:28,044} clusters in FIRM_id)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}     PROFITS{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}ETR {c |}{col 14}{res}{space 2}-.0107283{col 26}{space 2} .0002448{col 37}{space 1}  -43.82{col 46}{space 3}0.000{col 54}{space 4}-.0112081{col 67}{space 3}-.0102484
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 10.33206{col 26}{space 2}   .04363{col 37}{space 1}  236.81{col 46}{space 3}0.000{col 54}{space 4} 10.24655{col 67}{space 3} 10.41757
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}/lndelta {c |}{col 14}{res}{space 2} 11.24196{col 26}{space 2} .0632436{col 54}{space 4}   11.118{col 67}{space 3} 11.36591
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
       delta {c |}{col 14}{res}{space 2} 76264.02{col 26}{space 2}  4823.21{col 54}{space 4} 67373.12{col 67}{space 3} 86328.21
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. nbreg PROFITS ETR lnSALES lnEMP lnGDP lnKLRAT lnSKILL lnLABOR lnMARK lnPOPDEN ///
>       lnINFRAS lnFINANCE lnINVFOR y2006-y2009 if insample == 1, dispersion(constant) vce(cluster FIRM_id)

{txt}Fitting Poisson model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-1.688e+09}  
Iteration 1:{space 3}log pseudolikelihood = {res:-7.141e+08}  
Iteration 2:{space 3}log pseudolikelihood = {res:-5.123e+08}  
Iteration 3:{space 3}log pseudolikelihood = {res:-5.113e+08}  
Iteration 4:{space 3}log pseudolikelihood = {res:-5.113e+08}  
Iteration 5:{space 3}log pseudolikelihood = {res:-5.113e+08}  
{res}
{txt}Fitting constant-only model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-1.025e+09}  
Iteration 1:{space 3}log pseudolikelihood = {res:-664012.76}  
Iteration 2:{space 3}log pseudolikelihood = {res:-603707.51}  
Iteration 3:{space 3}log pseudolikelihood = {res: -603445.4}  
Iteration 4:{space 3}log pseudolikelihood = {res:-603444.81}  
Iteration 5:{space 3}log pseudolikelihood = {res:-603444.81}  
{res}
{txt}Fitting full model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-603444.81}  
Iteration 1:{space 3}log pseudolikelihood = {res: -589437.3}  
Iteration 2:{space 3}log pseudolikelihood = {res:-586089.45}  
Iteration 3:{space 3}log pseudolikelihood = {res:-585322.93}  
Iteration 4:{space 3}log pseudolikelihood = {res: -585314.6}  
Iteration 5:{space 3}log pseudolikelihood = {res:-585314.59}  
{res}
{txt}Negative binomial regression{col 49}Number of obs{col 67}= {res}    57,802
{txt}{col 49}Wald chi2({res}16{txt}){col 67}= {res}   3143.51
{txt}{col 1}Dispersion{col 22}= {res}constant{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log pseudolikelihood = {res}-585314.59{txt}{col 49}Pseudo R2{col 67}= {res}    0.0300

{txt}{ralign 78:(Std. Err. adjusted for {res:28,044} clusters in FIRM_id)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}     PROFITS{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}ETR {c |}{col 14}{res}{space 2}-.0104416{col 26}{space 2} .0005163{col 37}{space 1}  -20.22{col 46}{space 3}0.000{col 54}{space 4}-.0114536{col 67}{space 3}-.0094296
{txt}{space 5}lnSALES {c |}{col 14}{res}{space 2} .5825194{col 26}{space 2} .0145654{col 37}{space 1}   39.99{col 46}{space 3}0.000{col 54}{space 4} .5539717{col 67}{space 3} .6110671
{txt}{space 7}lnEMP {c |}{col 14}{res}{space 2} .0452058{col 26}{space 2} .0115723{col 37}{space 1}    3.91{col 46}{space 3}0.000{col 54}{space 4} .0225245{col 67}{space 3} .0678871
{txt}{space 7}lnGDP {c |}{col 14}{res}{space 2} .1480206{col 26}{space 2} .0246638{col 37}{space 1}    6.00{col 46}{space 3}0.000{col 54}{space 4} .0996805{col 67}{space 3} .1963606
{txt}{space 5}lnKLRAT {c |}{col 14}{res}{space 2}  .086381{col 26}{space 2} .0080127{col 37}{space 1}   10.78{col 46}{space 3}0.000{col 54}{space 4} .0706764{col 67}{space 3} .1020856
{txt}{space 5}lnSKILL {c |}{col 14}{res}{space 2} .0231142{col 26}{space 2}  .019583{col 37}{space 1}    1.18{col 46}{space 3}0.238{col 54}{space 4}-.0152678{col 67}{space 3} .0614962
{txt}{space 5}lnLABOR {c |}{col 14}{res}{space 2}-.0636912{col 26}{space 2} .0755288{col 37}{space 1}   -0.84{col 46}{space 3}0.399{col 54}{space 4}-.2117249{col 67}{space 3} .0843425
{txt}{space 6}lnMARK {c |}{col 14}{res}{space 2} .1512696{col 26}{space 2} .0374793{col 37}{space 1}    4.04{col 46}{space 3}0.000{col 54}{space 4} .0778114{col 67}{space 3} .2247277
{txt}{space 4}lnPOPDEN {c |}{col 14}{res}{space 2}-.0583991{col 26}{space 2} .0224678{col 37}{space 1}   -2.60{col 46}{space 3}0.009{col 54}{space 4}-.1024353{col 67}{space 3} -.014363
{txt}{space 4}lnINFRAS {c |}{col 14}{res}{space 2} .0486111{col 26}{space 2} .0256722{col 37}{space 1}    1.89{col 46}{space 3}0.058{col 54}{space 4}-.0017054{col 67}{space 3} .0989276
{txt}{space 3}lnFINANCE {c |}{col 14}{res}{space 2}-.1718347{col 26}{space 2} .0317636{col 37}{space 1}   -5.41{col 46}{space 3}0.000{col 54}{space 4}-.2340902{col 67}{space 3}-.1095792
{txt}{space 4}lnINVFOR {c |}{col 14}{res}{space 2}-.0510745{col 26}{space 2} .0131737{col 37}{space 1}   -3.88{col 46}{space 3}0.000{col 54}{space 4}-.0768945{col 67}{space 3}-.0252545
{txt}{space 7}y2006 {c |}{col 14}{res}{space 2}-.0198753{col 26}{space 2} .0149888{col 37}{space 1}   -1.33{col 46}{space 3}0.185{col 54}{space 4}-.0492529{col 67}{space 3} .0095023
{txt}{space 7}y2007 {c |}{col 14}{res}{space 2}-.0277348{col 26}{space 2} .0268847{col 37}{space 1}   -1.03{col 46}{space 3}0.302{col 54}{space 4}-.0804279{col 67}{space 3} .0249583
{txt}{space 7}y2008 {c |}{col 14}{res}{space 2}-.0024751{col 26}{space 2} .0338155{col 37}{space 1}   -0.07{col 46}{space 3}0.942{col 54}{space 4}-.0687522{col 67}{space 3} .0638021
{txt}{space 7}y2009 {c |}{col 14}{res}{space 2} .0071154{col 26}{space 2} .0380077{col 37}{space 1}    0.19{col 46}{space 3}0.851{col 54}{space 4}-.0673783{col 67}{space 3} .0816091
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .8521949{col 26}{space 2} .8653215{col 37}{space 1}    0.98{col 46}{space 3}0.325{col 54}{space 4} -.843804{col 67}{space 3} 2.548194
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}/lndelta {c |}{col 14}{res}{space 2} 10.19758{col 26}{space 2} .0584166{col 54}{space 4} 10.08308{col 67}{space 3} 10.31207
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
       delta {c |}{col 14}{res}{space 2} 26838.07{col 26}{space 2} 1567.788{col 54}{space 4} 23934.65{col 67}{space 3}  30093.7
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. // This section produces the results for TABLE 5
. 
. // Here we see that ETR is correlated with lots of firm and region-related variables. 
. // This suggests that omitted variable bias is a potential explanation for the negative Profit-ETR relationship.
. reg ETR lnSALES lnEMP lnGDP lnKLRAT lnSKILL lnLABOR lnMARK lnPOPDEN lnINFRAS ///
>     lnFINANCE lnINVFOR y2006-y2009 if insample == 1, vce(cluster FIRM_id)

{txt}Linear regression                               Number of obs     = {res}    57,802
                                                {txt}F(15, 28043)      =  {res}    68.10
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0220
                                                {txt}Root MSE          =    {res}  12.58

{txt}{ralign 78:(Std. Err. adjusted for {res:28,044} clusters in FIRM_id)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}         ETR{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}lnSALES {c |}{col 14}{res}{space 2}  -1.0855{col 26}{space 2} .0700989{col 37}{space 1}  -15.49{col 46}{space 3}0.000{col 54}{space 4}-1.222897{col 67}{space 3}-.9481024
{txt}{space 7}lnEMP {c |}{col 14}{res}{space 2} .2665728{col 26}{space 2} .0850981{col 37}{space 1}    3.13{col 46}{space 3}0.002{col 54}{space 4} .0997763{col 67}{space 3} .4333693
{txt}{space 7}lnGDP {c |}{col 14}{res}{space 2} 1.666007{col 26}{space 2} .1926741{col 37}{space 1}    8.65{col 46}{space 3}0.000{col 54}{space 4} 1.288357{col 67}{space 3} 2.043658
{txt}{space 5}lnKLRAT {c |}{col 14}{res}{space 2} -.137771{col 26}{space 2} .0519204{col 37}{space 1}   -2.65{col 46}{space 3}0.008{col 54}{space 4}-.2395376{col 67}{space 3}-.0360044
{txt}{space 5}lnSKILL {c |}{col 14}{res}{space 2} -.043233{col 26}{space 2} .1328598{col 37}{space 1}   -0.33{col 46}{space 3}0.745{col 54}{space 4}-.3036447{col 67}{space 3} .2171787
{txt}{space 5}lnLABOR {c |}{col 14}{res}{space 2} .4102514{col 26}{space 2} .5455535{col 37}{space 1}    0.75{col 46}{space 3}0.452{col 54}{space 4}-.6590599{col 67}{space 3} 1.479563
{txt}{space 6}lnMARK {c |}{col 14}{res}{space 2}-.0376535{col 26}{space 2} .2449258{col 37}{space 1}   -0.15{col 46}{space 3}0.878{col 54}{space 4}-.5177199{col 67}{space 3}  .442413
{txt}{space 4}lnPOPDEN {c |}{col 14}{res}{space 2}-.4345541{col 26}{space 2} .1504575{col 37}{space 1}   -2.89{col 46}{space 3}0.004{col 54}{space 4}-.7294581{col 67}{space 3}-.1396501
{txt}{space 4}lnINFRAS {c |}{col 14}{res}{space 2} -.109828{col 26}{space 2} .1877345{col 37}{space 1}   -0.59{col 46}{space 3}0.559{col 54}{space 4}-.4777969{col 67}{space 3} .2581408
{txt}{space 3}lnFINANCE {c |}{col 14}{res}{space 2}-1.156985{col 26}{space 2}   .23334{col 37}{space 1}   -4.96{col 46}{space 3}0.000{col 54}{space 4}-1.614343{col 67}{space 3}-.6996273
{txt}{space 4}lnINVFOR {c |}{col 14}{res}{space 2}-.9252734{col 26}{space 2} .1075083{col 37}{space 1}   -8.61{col 46}{space 3}0.000{col 54}{space 4}-1.135995{col 67}{space 3}-.7145519
{txt}{space 7}y2006 {c |}{col 14}{res}{space 2}-.1945668{col 26}{space 2} .1670468{col 37}{space 1}   -1.16{col 46}{space 3}0.244{col 54}{space 4}-.5219866{col 67}{space 3}  .132853
{txt}{space 7}y2007 {c |}{col 14}{res}{space 2}-.1603194{col 26}{space 2} .2202445{col 37}{space 1}   -0.73{col 46}{space 3}0.467{col 54}{space 4}-.5920094{col 67}{space 3} .2713705
{txt}{space 7}y2008 {c |}{col 14}{res}{space 2} .5544311{col 26}{space 2}  .256435{col 37}{space 1}    2.16{col 46}{space 3}0.031{col 54}{space 4} .0518061{col 67}{space 3} 1.057056
{txt}{space 7}y2009 {c |}{col 14}{res}{space 2} 1.291725{col 26}{space 2} .2901654{col 37}{space 1}    4.45{col 46}{space 3}0.000{col 54}{space 4} .7229865{col 67}{space 3} 1.860463
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-.0326706{col 26}{space 2} 5.491665{col 37}{space 1}   -0.01{col 46}{space 3}0.995{col 54}{space 4} -10.7966{col 67}{space 3} 10.73126
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. test (lnSALES lnEMP lnGDP lnKLRAT lnSKILL lnLABOR lnMARK lnPOPDEN lnINFRAS ///
>     lnFINANCE lnINVFOR)

{p 0 7}{space 1}{text:( 1)}{space 1} {res}lnSALES = 0{p_end}
{p 0 7}{space 1}{text:( 2)}{space 1} lnEMP = 0{p_end}
{p 0 7}{space 1}{text:( 3)}{space 1} lnGDP = 0{p_end}
{p 0 7}{space 1}{text:( 4)}{space 1} lnKLRAT = 0{p_end}
{p 0 7}{space 1}{text:( 5)}{space 1} lnSKILL = 0{p_end}
{p 0 7}{space 1}{text:( 6)}{space 1} lnLABOR = 0{p_end}
{p 0 7}{space 1}{text:( 7)}{space 1} lnMARK = 0{p_end}
{p 0 7}{space 1}{text:( 8)}{space 1} lnPOPDEN = 0{p_end}
{p 0 7}{space 1}{text:( 9)}{space 1} lnINFRAS = 0{p_end}
{p 0 7}{space 1}{text:(10)}{space 1} lnFINANCE = 0{p_end}
{p 0 7}{space 1}{text:(11)}{space 1} lnINVFOR = 0{p_end}

{txt}       F( 11, 28043) ={res}   76.52
{txt}{col 13}Prob > F ={res}    0.0000
{txt}
{com}.         
. 
. // This regression allows us to see average ETR values by year.
. // Note no significant difference in ETR in the pre-law change years (2005, 2006, 2007) 
. // but significant increases in 2008 and 2009 
. regress ETR y2006-y2009 if insample == 1, vce(cluster FIRM_id)    

{txt}Linear regression                               Number of obs     = {res}    57,802
                                                {txt}F(4, 28043)       =  {res}    37.12
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0027
                                                {txt}Root MSE          =    {res} 12.701

{txt}{ralign 78:(Std. Err. adjusted for {res:28,044} clusters in FIRM_id)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}         ETR{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}y2006 {c |}{col 14}{res}{space 2} -.239105{col 26}{space 2} .1566879{col 37}{space 1}   -1.53{col 46}{space 3}0.127{col 54}{space 4} -.546221{col 67}{space 3}  .068011
{txt}{space 7}y2007 {c |}{col 14}{res}{space 2}-.2473138{col 26}{space 2} .1617752{col 37}{space 1}   -1.53{col 46}{space 3}0.126{col 54}{space 4}-.5644011{col 67}{space 3} .0697736
{txt}{space 7}y2008 {c |}{col 14}{res}{space 2} .5641664{col 26}{space 2} .1737271{col 37}{space 1}    3.25{col 46}{space 3}0.001{col 54}{space 4}  .223653{col 67}{space 3} .9046799
{txt}{space 7}y2009 {c |}{col 14}{res}{space 2} 1.457415{col 26}{space 2} .1721827{col 37}{space 1}    8.46{col 46}{space 3}0.000{col 54}{space 4} 1.119928{col 67}{space 3} 1.794901
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 17.94161{col 26}{space 2}  .130545{col 37}{space 1}  137.44{col 46}{space 3}0.000{col 54}{space 4} 17.68573{col 67}{space 3} 18.19748
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. test (y2006 y2007)

{p 0 7}{space 1}{text:( 1)}{space 1} {res}y2006 = 0{p_end}
{p 0 7}{space 1}{text:( 2)}{space 1} y2007 = 0{p_end}

{txt}       F(  2, 28043) ={res}    1.47
{txt}{col 13}Prob > F ={res}    0.2300
{txt}
{com}. 
. // This section produces the results for TABLE 6, though the test of equality of ETR
. // coefficients is reported in TABLE 7
. 
. // We next determine if there are two groups of profit-shifters
. nbreg PROFITS ETR lnSALES lnEMP lnGDP lnKLRAT lnSKILL lnLABOR lnMARK lnPOPDEN ///
>       lnINFRAS lnFINANCE lnINVFOR y2006-y2009 if insample == 1, dispersion(constant) vce(cluster FIRM_id)

{txt}Fitting Poisson model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-1.688e+09}  
Iteration 1:{space 3}log pseudolikelihood = {res:-7.141e+08}  
Iteration 2:{space 3}log pseudolikelihood = {res:-5.123e+08}  
Iteration 3:{space 3}log pseudolikelihood = {res:-5.113e+08}  
Iteration 4:{space 3}log pseudolikelihood = {res:-5.113e+08}  
Iteration 5:{space 3}log pseudolikelihood = {res:-5.113e+08}  
{res}
{txt}Fitting constant-only model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-1.025e+09}  
Iteration 1:{space 3}log pseudolikelihood = {res:-664012.76}  
Iteration 2:{space 3}log pseudolikelihood = {res:-603707.51}  
Iteration 3:{space 3}log pseudolikelihood = {res: -603445.4}  
Iteration 4:{space 3}log pseudolikelihood = {res:-603444.81}  
Iteration 5:{space 3}log pseudolikelihood = {res:-603444.81}  
{res}
{txt}Fitting full model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-603444.81}  
Iteration 1:{space 3}log pseudolikelihood = {res: -589437.3}  
Iteration 2:{space 3}log pseudolikelihood = {res:-586089.45}  
Iteration 3:{space 3}log pseudolikelihood = {res:-585322.93}  
Iteration 4:{space 3}log pseudolikelihood = {res: -585314.6}  
Iteration 5:{space 3}log pseudolikelihood = {res:-585314.59}  
{res}
{txt}Negative binomial regression{col 49}Number of obs{col 67}= {res}    57,802
{txt}{col 49}Wald chi2({res}16{txt}){col 67}= {res}   3143.51
{txt}{col 1}Dispersion{col 22}= {res}constant{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log pseudolikelihood = {res}-585314.59{txt}{col 49}Pseudo R2{col 67}= {res}    0.0300

{txt}{ralign 78:(Std. Err. adjusted for {res:28,044} clusters in FIRM_id)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}     PROFITS{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}ETR {c |}{col 14}{res}{space 2}-.0104416{col 26}{space 2} .0005163{col 37}{space 1}  -20.22{col 46}{space 3}0.000{col 54}{space 4}-.0114536{col 67}{space 3}-.0094296
{txt}{space 5}lnSALES {c |}{col 14}{res}{space 2} .5825194{col 26}{space 2} .0145654{col 37}{space 1}   39.99{col 46}{space 3}0.000{col 54}{space 4} .5539717{col 67}{space 3} .6110671
{txt}{space 7}lnEMP {c |}{col 14}{res}{space 2} .0452058{col 26}{space 2} .0115723{col 37}{space 1}    3.91{col 46}{space 3}0.000{col 54}{space 4} .0225245{col 67}{space 3} .0678871
{txt}{space 7}lnGDP {c |}{col 14}{res}{space 2} .1480206{col 26}{space 2} .0246638{col 37}{space 1}    6.00{col 46}{space 3}0.000{col 54}{space 4} .0996805{col 67}{space 3} .1963606
{txt}{space 5}lnKLRAT {c |}{col 14}{res}{space 2}  .086381{col 26}{space 2} .0080127{col 37}{space 1}   10.78{col 46}{space 3}0.000{col 54}{space 4} .0706764{col 67}{space 3} .1020856
{txt}{space 5}lnSKILL {c |}{col 14}{res}{space 2} .0231142{col 26}{space 2}  .019583{col 37}{space 1}    1.18{col 46}{space 3}0.238{col 54}{space 4}-.0152678{col 67}{space 3} .0614962
{txt}{space 5}lnLABOR {c |}{col 14}{res}{space 2}-.0636912{col 26}{space 2} .0755288{col 37}{space 1}   -0.84{col 46}{space 3}0.399{col 54}{space 4}-.2117249{col 67}{space 3} .0843425
{txt}{space 6}lnMARK {c |}{col 14}{res}{space 2} .1512696{col 26}{space 2} .0374793{col 37}{space 1}    4.04{col 46}{space 3}0.000{col 54}{space 4} .0778114{col 67}{space 3} .2247277
{txt}{space 4}lnPOPDEN {c |}{col 14}{res}{space 2}-.0583991{col 26}{space 2} .0224678{col 37}{space 1}   -2.60{col 46}{space 3}0.009{col 54}{space 4}-.1024353{col 67}{space 3} -.014363
{txt}{space 4}lnINFRAS {c |}{col 14}{res}{space 2} .0486111{col 26}{space 2} .0256722{col 37}{space 1}    1.89{col 46}{space 3}0.058{col 54}{space 4}-.0017054{col 67}{space 3} .0989276
{txt}{space 3}lnFINANCE {c |}{col 14}{res}{space 2}-.1718347{col 26}{space 2} .0317636{col 37}{space 1}   -5.41{col 46}{space 3}0.000{col 54}{space 4}-.2340902{col 67}{space 3}-.1095792
{txt}{space 4}lnINVFOR {c |}{col 14}{res}{space 2}-.0510745{col 26}{space 2} .0131737{col 37}{space 1}   -3.88{col 46}{space 3}0.000{col 54}{space 4}-.0768945{col 67}{space 3}-.0252545
{txt}{space 7}y2006 {c |}{col 14}{res}{space 2}-.0198753{col 26}{space 2} .0149888{col 37}{space 1}   -1.33{col 46}{space 3}0.185{col 54}{space 4}-.0492529{col 67}{space 3} .0095023
{txt}{space 7}y2007 {c |}{col 14}{res}{space 2}-.0277348{col 26}{space 2} .0268847{col 37}{space 1}   -1.03{col 46}{space 3}0.302{col 54}{space 4}-.0804279{col 67}{space 3} .0249583
{txt}{space 7}y2008 {c |}{col 14}{res}{space 2}-.0024751{col 26}{space 2} .0338155{col 37}{space 1}   -0.07{col 46}{space 3}0.942{col 54}{space 4}-.0687522{col 67}{space 3} .0638021
{txt}{space 7}y2009 {c |}{col 14}{res}{space 2} .0071154{col 26}{space 2} .0380077{col 37}{space 1}    0.19{col 46}{space 3}0.851{col 54}{space 4}-.0673783{col 67}{space 3} .0816091
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .8521949{col 26}{space 2} .8653215{col 37}{space 1}    0.98{col 46}{space 3}0.325{col 54}{space 4} -.843804{col 67}{space 3} 2.548194
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}/lndelta {c |}{col 14}{res}{space 2} 10.19758{col 26}{space 2} .0584166{col 54}{space 4} 10.08308{col 67}{space 3} 10.31207
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
       delta {c |}{col 14}{res}{space 2} 26838.07{col 26}{space 2} 1567.788{col 54}{space 4} 23934.65{col 67}{space 3}  30093.7
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. est store component1
{txt}
{com}. estat ic

Akaike's information criterion and Bayesian information criterion

{txt}{hline 13}{c TT}{hline 63}
       Model {c |}        Obs  ll(null)  ll(model)      df         AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:{stata estimates replay component1:component1}}{col 14}{c |}{res}{col 16}    57,802{col 27}-603444.8{col 38}-585314.6{col 49}    18{col 58}  1170665{col 69}  1170827
{txt}{hline 13}{c BT}{hline 63}
{p 15 21 2}
Note: N=Obs used in calculating BIC; see {helpb bic_note:[R] BIC note}.
{p_end}

{com}. matrix comp1 = r(S)
{txt}
{com}. 
. // This is the 2-component FMM. We find that the first group has a smaller investment tax elasticity
. fmm 2 if insample == 1, vce(cluster FIRM_id)  : nbreg PROFITS ETR lnSALES lnEMP ///
>       lnGDP lnKLRAT lnSKILL lnLABOR lnMARK lnPOPDEN lnINFRAS lnFINANCE lnINVFOR y2006-y2009 , dispersion(constant)
{res}{txt}
Fitting class model:

Iteration 0:{space 3}(class) log likelihood = {res:-40065.293}  
Iteration 1:{space 3}(class) log likelihood = {res:-40065.293}  

Fitting outcome model:

Iteration 0:{space 3}(outcome) log likelihood = {res:-4.128e+08}  (not concave)
Iteration 1:{space 3}(outcome) log likelihood = {res:-721950.89}  (not concave)
Iteration 2:{space 3}(outcome) log likelihood = {res:-669249.75}  (not concave)
Iteration 3:{space 3}(outcome) log likelihood = {res: -606392.3}  (not concave)
Iteration 4:{space 3}(outcome) log likelihood = {res:-592134.01}  
Iteration 5:{space 3}(outcome) log likelihood = {res:-590978.83}  
Iteration 6:{space 3}(outcome) log likelihood = {res:-584075.25}  
Iteration 7:{space 3}(outcome) log likelihood = {res:-583878.41}  
Iteration 8:{space 3}(outcome) log likelihood = {res:-583877.73}  
Iteration 9:{space 3}(outcome) log likelihood = {res:-583877.73}  

Refining starting values:

Iteration 0:{space 3}(EM) log likelihood = {res:-616848.85}
Iteration 1:{space 3}(EM) log likelihood = {res:-607813.91}
Iteration 2:{space 3}(EM) log likelihood = {res:-599839.43}
Iteration 3:{space 3}(EM) log likelihood = {res:-594691.48}
Iteration 4:{space 3}(EM) log likelihood = {res:-591942.12}
Iteration 5:{space 3}(EM) log likelihood = {res:-590542.51}
Iteration 6:{space 3}(EM) log likelihood = {res: -589786.7}
Iteration 7:{space 3}(EM) log likelihood = {res:-589325.67}
Iteration 8:{space 3}(EM) log likelihood = {res:-589004.38}
Iteration 9:{space 3}(EM) log likelihood = {res:-588755.81}
Iteration 10:{space 2}(EM) log likelihood = {res:-588550.61}
Iteration 11:{space 2}(EM) log likelihood = {res:-588375.26}
Iteration 12:{space 2}(EM) log likelihood = {res:-588222.95}
Iteration 13:{space 2}(EM) log likelihood = {res:-588089.78}
Iteration 14:{space 2}(EM) log likelihood = {res:-587973.14}
Iteration 15:{space 2}(EM) log likelihood = {res:   -587871}
Iteration 16:{space 2}(EM) log likelihood = {res:-587781.63}
Iteration 17:{space 2}(EM) log likelihood = {res:-587703.54}
Iteration 18:{space 2}(EM) log likelihood = {res:-587635.34}
Iteration 19:{space 2}(EM) log likelihood = {res:-587575.82}
Iteration 20:{space 2}(EM) log likelihood = {res:-587523.98}
{p}
Note: EM algorithm reached maximum iterations.
{p_end}

Fitting full model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-568584.94}  
Iteration 1:{space 3}log pseudolikelihood = {res:-568583.19}  
Iteration 2:{space 3}log pseudolikelihood = {res:-568583.19}  
{res}
{txt}Finite mixture model{col 49}Number of obs{col 67}= {res}    57,802
{txt}Log pseudolikelihood = {res}-568583.19

{txt}{ralign 78:(Std. Err. adjusted for {res:28,044} clusters in FIRM_id)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}1.Class     {col 14}{txt}{c |}  (base outcome)
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}2.Class      {txt}{c |}
{space 7}_cons {c |}{col 14}{res}{space 2}-1.336965{col 26}{space 2} .0691814{col 37}{space 1}  -19.33{col 46}{space 3}0.000{col 54}{space 4}-1.472558{col 67}{space 3}-1.201372
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Class{col 16}: {res}1
{txt}Response{col 16}: {res}PROFITS
{txt}Model{col 16}: {res}nbreg, dispersion(constant)

{txt}{ralign 78:(Std. Err. adjusted for {res:28,044} clusters in FIRM_id)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}PROFITS      {txt}{c |}
{space 9}ETR {c |}{col 14}{res}{space 2}-.0145755{col 26}{space 2} .0005031{col 37}{space 1}  -28.97{col 46}{space 3}0.000{col 54}{space 4}-.0155615{col 67}{space 3}-.0135894
{txt}{space 5}lnSALES {c |}{col 14}{res}{space 2}  .713734{col 26}{space 2} .0133409{col 37}{space 1}   53.50{col 46}{space 3}0.000{col 54}{space 4} .6875864{col 67}{space 3} .7398817
{txt}{space 7}lnEMP {c |}{col 14}{res}{space 2}-.0237564{col 26}{space 2} .0099103{col 37}{space 1}   -2.40{col 46}{space 3}0.017{col 54}{space 4}-.0431802{col 67}{space 3}-.0043326
{txt}{space 7}lnGDP {c |}{col 14}{res}{space 2} .1693794{col 26}{space 2} .0197667{col 37}{space 1}    8.57{col 46}{space 3}0.000{col 54}{space 4} .1306375{col 67}{space 3} .2081214
{txt}{space 5}lnKLRAT {c |}{col 14}{res}{space 2} .0952756{col 26}{space 2} .0064575{col 37}{space 1}   14.75{col 46}{space 3}0.000{col 54}{space 4} .0826191{col 67}{space 3}  .107932
{txt}{space 5}lnSKILL {c |}{col 14}{res}{space 2} .0585185{col 26}{space 2}  .017482{col 37}{space 1}    3.35{col 46}{space 3}0.001{col 54}{space 4} .0242543{col 67}{space 3} .0927827
{txt}{space 5}lnLABOR {c |}{col 14}{res}{space 2}-.2239008{col 26}{space 2} .0577866{col 37}{space 1}   -3.87{col 46}{space 3}0.000{col 54}{space 4}-.3371605{col 67}{space 3}-.1106411
{txt}{space 6}lnMARK {c |}{col 14}{res}{space 2}  .229114{col 26}{space 2} .0307155{col 37}{space 1}    7.46{col 46}{space 3}0.000{col 54}{space 4} .1689127{col 67}{space 3} .2893152
{txt}{space 4}lnPOPDEN {c |}{col 14}{res}{space 2}-.0157348{col 26}{space 2}  .019941{col 37}{space 1}   -0.79{col 46}{space 3}0.430{col 54}{space 4}-.0548186{col 67}{space 3} .0233489
{txt}{space 4}lnINFRAS {c |}{col 14}{res}{space 2} .0181115{col 26}{space 2} .0234694{col 37}{space 1}    0.77{col 46}{space 3}0.440{col 54}{space 4}-.0278878{col 67}{space 3} .0641108
{txt}{space 3}lnFINANCE {c |}{col 14}{res}{space 2} -.206958{col 26}{space 2} .0296377{col 37}{space 1}   -6.98{col 46}{space 3}0.000{col 54}{space 4}-.2650467{col 67}{space 3}-.1488692
{txt}{space 4}lnINVFOR {c |}{col 14}{res}{space 2}-.0174171{col 26}{space 2} .0122693{col 37}{space 1}   -1.42{col 46}{space 3}0.156{col 54}{space 4}-.0414645{col 67}{space 3} .0066304
{txt}{space 7}y2006 {c |}{col 14}{res}{space 2}-.0135487{col 26}{space 2} .0163746{col 37}{space 1}   -0.83{col 46}{space 3}0.408{col 54}{space 4}-.0456424{col 67}{space 3}  .018545
{txt}{space 7}y2007 {c |}{col 14}{res}{space 2}-.0124987{col 26}{space 2} .0224621{col 37}{space 1}   -0.56{col 46}{space 3}0.578{col 54}{space 4}-.0565237{col 67}{space 3} .0315262
{txt}{space 7}y2008 {c |}{col 14}{res}{space 2} .0078105{col 26}{space 2} .0270103{col 37}{space 1}    0.29{col 46}{space 3}0.772{col 54}{space 4}-.0451288{col 67}{space 3} .0607498
{txt}{space 7}y2009 {c |}{col 14}{res}{space 2} .0393723{col 26}{space 2} .0303228{col 37}{space 1}    1.30{col 46}{space 3}0.194{col 54}{space 4}-.0200594{col 67}{space 3} .0988039
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-.5163223{col 26}{space 2} .6744341{col 37}{space 1}   -0.77{col 46}{space 3}0.444{col 54}{space 4}-1.838189{col 67}{space 3} .8055441
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}/PROFITS     {txt}{c |}
{space 5}lndelta {c |}{col 14}{res}{space 2} 8.160768{col 26}{space 2} .0434015{col 54}{space 4} 8.075702{col 67}{space 3} 8.245833
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Class{col 16}: {res}2
{txt}Response{col 16}: {res}PROFITS
{txt}Model{col 16}: {res}nbreg, dispersion(constant)

{txt}{ralign 78:(Std. Err. adjusted for {res:28,044} clusters in FIRM_id)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}PROFITS      {txt}{c |}
{space 9}ETR {c |}{col 14}{res}{space 2}-.0106338{col 26}{space 2} .0010798{col 37}{space 1}   -9.85{col 46}{space 3}0.000{col 54}{space 4}-.0127501{col 67}{space 3}-.0085174
{txt}{space 5}lnSALES {c |}{col 14}{res}{space 2} .4750567{col 26}{space 2} .0222973{col 37}{space 1}   21.31{col 46}{space 3}0.000{col 54}{space 4} .4313549{col 67}{space 3} .5187586
{txt}{space 7}lnEMP {c |}{col 14}{res}{space 2} .0962843{col 26}{space 2} .0192133{col 37}{space 1}    5.01{col 46}{space 3}0.000{col 54}{space 4} .0586268{col 67}{space 3} .1339418
{txt}{space 7}lnGDP {c |}{col 14}{res}{space 2} .1354147{col 26}{space 2} .0442254{col 37}{space 1}    3.06{col 46}{space 3}0.002{col 54}{space 4} .0487344{col 67}{space 3}  .222095
{txt}{space 5}lnKLRAT {c |}{col 14}{res}{space 2} .0884775{col 26}{space 2} .0139772{col 37}{space 1}    6.33{col 46}{space 3}0.000{col 54}{space 4} .0610826{col 67}{space 3} .1158723
{txt}{space 5}lnSKILL {c |}{col 14}{res}{space 2} .0157939{col 26}{space 2} .0332911{col 37}{space 1}    0.47{col 46}{space 3}0.635{col 54}{space 4}-.0494554{col 67}{space 3} .0810432
{txt}{space 5}lnLABOR {c |}{col 14}{res}{space 2} .0518288{col 26}{space 2} .1303433{col 37}{space 1}    0.40{col 46}{space 3}0.691{col 54}{space 4}-.2036394{col 67}{space 3}  .307297
{txt}{space 6}lnMARK {c |}{col 14}{res}{space 2} .1162749{col 26}{space 2} .0640566{col 37}{space 1}    1.82{col 46}{space 3}0.069{col 54}{space 4}-.0092738{col 67}{space 3} .2418236
{txt}{space 4}lnPOPDEN {c |}{col 14}{res}{space 2}-.0645938{col 26}{space 2}  .036199{col 37}{space 1}   -1.78{col 46}{space 3}0.074{col 54}{space 4}-.1355426{col 67}{space 3}  .006355
{txt}{space 4}lnINFRAS {c |}{col 14}{res}{space 2} .0381933{col 26}{space 2} .0437786{col 37}{space 1}    0.87{col 46}{space 3}0.383{col 54}{space 4}-.0476113{col 67}{space 3} .1239978
{txt}{space 3}lnFINANCE {c |}{col 14}{res}{space 2}-.1271627{col 26}{space 2}  .055074{col 37}{space 1}   -2.31{col 46}{space 3}0.021{col 54}{space 4}-.2351059{col 67}{space 3}-.0192196
{txt}{space 4}lnINVFOR {c |}{col 14}{res}{space 2}-.0839971{col 26}{space 2} .0235332{col 37}{space 1}   -3.57{col 46}{space 3}0.000{col 54}{space 4}-.1301215{col 67}{space 3}-.0378728
{txt}{space 7}y2006 {c |}{col 14}{res}{space 2}-.0117223{col 26}{space 2} .0322588{col 37}{space 1}   -0.36{col 46}{space 3}0.716{col 54}{space 4}-.0749484{col 67}{space 3} .0515037
{txt}{space 7}y2007 {c |}{col 14}{res}{space 2}-.0178957{col 26}{space 2} .0486137{col 37}{space 1}   -0.37{col 46}{space 3}0.713{col 54}{space 4}-.1131768{col 67}{space 3} .0773853
{txt}{space 7}y2008 {c |}{col 14}{res}{space 2}-.0016331{col 26}{space 2} .0600455{col 37}{space 1}   -0.03{col 46}{space 3}0.978{col 54}{space 4}  -.11932{col 67}{space 3} .1160538
{txt}{space 7}y2009 {c |}{col 14}{res}{space 2} .0173265{col 26}{space 2} .0665317{col 37}{space 1}    0.26{col 46}{space 3}0.795{col 54}{space 4}-.1130732{col 67}{space 3} .1477262
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 2.076239{col 26}{space 2} 1.417322{col 37}{space 1}    1.46{col 46}{space 3}0.143{col 54}{space 4}-.7016607{col 67}{space 3} 4.854139
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}/PROFITS     {txt}{c |}
{space 5}lndelta {c |}{col 14}{res}{space 2} 11.56717{col 26}{space 2} .1095021{col 54}{space 4} 11.35255{col 67}{space 3} 11.78179
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. test _b[PROFITS:2.Class#c.ETR] - _b[PROFITS:1.Class#c.ETR]==0

{p 0 7}{space 1}{text:( 1)}{space 1}{space 1}{res}- [PROFITS]1bn.Class#c.ETR + [PROFITS]2.Class#c.ETR = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    9.09
{txt}{col 10}Prob > chi2 =  {res}  0.0026
{txt}
{com}. est store component2
{txt}
{com}. estat ic

Akaike's information criterion and Bayesian information criterion

{txt}{hline 13}{c TT}{hline 63}
       Model {c |}        Obs  ll(null)  ll(model)      df         AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:{stata estimates replay component2:component2}}{col 14}{c |}{res}{col 16}    57,802{col 27}        .{col 38}-568583.2{col 49}    37{col 58}  1137240{col 69}  1137572
{txt}{hline 13}{c BT}{hline 63}
{p 15 21 2}
Note: N=Obs used in calculating BIC; see {helpb bic_note:[R] BIC note}.
{p_end}

{com}. matrix comp2 = r(S)
{txt}
{com}.         
. // Evidence that the 2 component model is better that 1 component model
. matrix list comp1 
{res}
{txt}comp1[1,6]
                     N         ll0          ll          df         AIC         BIC
component1 {res}      57802  -603444.81  -585314.59          18   1170665.2   1170826.6
{reset}
{com}. matrix list comp2
{res}
{txt}comp2[1,6]
                     N         ll0          ll          df         AIC         BIC
component2 {res}      57802           .  -568583.19          37   1137240.4   1137572.1
{reset}
{com}. lrtest component1 component2, force

{txt}Likelihood-ratio test{col 55}LR chi2({res}19{txt}){col 67}={res}  33462.81
{txt}(Assumption: {res}{stata est replay component1:component1}{txt} nested in {res}{stata est replay component2:component2}{txt}){col 55}Prob > chi2 = {res}   0.0000
{txt}
{com}. 
. // This section produces the results for TABLE 7
. 
. // Characteristics of each group
. predict fmmpos1 if insample == 1 , classposteriorpr class(1) 
{res}{txt}(83356 missing values generated)

{com}. predict fmmpos2 if insample == 1, classposteriorpr class(2)   
{res}{txt}(83356 missing values generated)

{com}. count if fmmpos1>fmmpos2  
  {res}50,716
{txt}
{com}. scalar group1 = r(N)
{txt}
{com}. count if fmmpos1<fmmpos2
  {res}7,086
{txt}
{com}. scalar group2 = r(N)    
{txt}
{com}. scalar pctgroup1 = group1/(group1+group2)
{txt}
{com}. scalar pctgroup2 = group2/(group1+group2)
{txt}
{com}. display pctgroup1 pctgroup2
{res}.87740909.12259091
{txt}
{com}. 
. // Creating dummy variables to identify both groups
. gen group1=(fmmpos1>fmmpos2)
{txt}
{com}. gen group2=(fmmpos1<fmmpos2)
{txt}
{com}. 
. summ PROFITS if group1 == 1

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 5}PROFITS {c |}{res}     50,716    7659.634    15604.84          2     701859
{txt}
{com}. scalar TOTALPROFITS1 = r(N)*r(mean)
{txt}
{com}. summ ASSETS if group1 == 1

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 6}ASSETS {c |}{res}     50,713    31912.86    127157.3          1   1.22e+07
{txt}
{com}. scalar TOTALASSETS1 = r(N)*r(mean)
{txt}
{com}. 
. summ PROFITS if group2 == 1

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 5}PROFITS {c |}{res}      7,086    152821.2      435020          2   1.47e+07
{txt}
{com}. scalar TOTALPROFITS2 = r(N)*r(mean)
{txt}
{com}. summ ASSETS if group2 == 1

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 6}ASSETS {c |}{res}      7,086    332558.1     1108193          5   2.53e+07
{txt}
{com}. scalar TOTALASSETS2 = r(N)*r(mean)
{txt}
{com}. 
. scalar PROFITSHARE1 = 100*TOTALPROFITS1/(TOTALPROFITS1 + TOTALPROFITS2)
{txt}
{com}. scalar ASSETSHARE1 = 100*TOTALASSETS1/(TOTALASSETS1 + TOTALASSETS2)
{txt}
{com}. scalar list PROFITSHARE1 ASSETSHARE1
{txt}PROFITSHARE1 = {res} 26.401882
{txt}ASSETSHARE1 = {res} 40.715369
{txt}
{com}. 
. summ ASSETS PROFITS EMP SALES if group1 == 1

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 6}ASSETS {c |}{res}     50,713    31912.86    127157.3          1   1.22e+07
{txt}{space 5}PROFITS {c |}{res}     50,716    7659.634    15604.84          2     701859
{txt}{space 9}EMP {c |}{res}     50,716    304.9162    660.8291          9      52440
{txt}{space 7}SALES {c |}{res}     50,716    138831.9    500022.8         41   2.93e+07
{txt}
{com}. 
. scalar PROFITSHARE2 = 100*TOTALPROFITS2/(TOTALPROFITS1 + TOTALPROFITS2)
{txt}
{com}. scalar ASSETSHARE2 = 100*TOTALASSETS2/(TOTALASSETS1 + TOTALASSETS2)
{txt}
{com}. scalar list PROFITSHARE2 ASSETSHARE2
{txt}PROFITSHARE2 = {res} 73.598118
{txt}ASSETSHARE2 = {res} 59.284631
{txt}
{com}. 
. summ ASSETS PROFITS EMP SALES if group2 == 1

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 6}ASSETS {c |}{res}      7,086    332558.1     1108193          5   2.53e+07
{txt}{space 5}PROFITS {c |}{res}      7,086    152821.2      435020          2   1.47e+07
{txt}{space 9}EMP {c |}{res}      7,086     1272.56    4737.234          9     198971
{txt}{space 7}SALES {c |}{res}      7,086     1673586     6537835        890   1.92e+08
{txt}
{com}. 
. // CONCLUSION: While first group has the larger tax elasticity, suggesting it consists
. // of profit shifters, it also is the largest group, with smaller assets, profits, employees,
. // and sales, inconsistent with this group being profit shifters
. 
. // This section produces the results for TABLE 8
. 
. gen treatdum = (year>2007)
{txt}
{com}. gen ETRxTD = ETR*treatdum
{txt}
{com}. 
. // We add an interaction term to see if there is a difference in tax elasticity after the law change. There isn't.
. nbreg PROFITS ETR ETRxTD lnSALES lnEMP lnGDP lnKLRAT lnSKILL lnLABOR lnMARK lnPOPDEN ///
>       lnINFRAS lnFINANCE lnINVFOR y2006-y2009 if insample == 1, dispersion(constant) vce(cluster FIRM_id)

{txt}Fitting Poisson model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-1.690e+09}  
Iteration 1:{space 3}log pseudolikelihood = {res:-7.151e+08}  
Iteration 2:{space 3}log pseudolikelihood = {res:-5.121e+08}  
Iteration 3:{space 3}log pseudolikelihood = {res:-5.111e+08}  
Iteration 4:{space 3}log pseudolikelihood = {res:-5.111e+08}  
Iteration 5:{space 3}log pseudolikelihood = {res:-5.111e+08}  
{res}
{txt}Fitting constant-only model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-1.025e+09}  
Iteration 1:{space 3}log pseudolikelihood = {res:-664012.76}  
Iteration 2:{space 3}log pseudolikelihood = {res:-603707.51}  
Iteration 3:{space 3}log pseudolikelihood = {res: -603445.4}  
Iteration 4:{space 3}log pseudolikelihood = {res:-603444.81}  
Iteration 5:{space 3}log pseudolikelihood = {res:-603444.81}  
{res}
{txt}Fitting full model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-603444.81}  
Iteration 1:{space 3}log pseudolikelihood = {res:-589432.12}  
Iteration 2:{space 3}log pseudolikelihood = {res:-586084.27}  
Iteration 3:{space 3}log pseudolikelihood = {res: -585310.9}  
Iteration 4:{space 3}log pseudolikelihood = {res:-585302.27}  
Iteration 5:{space 3}log pseudolikelihood = {res:-585302.26}  
{res}
{txt}Negative binomial regression{col 49}Number of obs{col 67}= {res}    57,802
{txt}{col 49}Wald chi2({res}17{txt}){col 67}= {res}   3177.63
{txt}{col 1}Dispersion{col 22}= {res}constant{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log pseudolikelihood = {res}-585302.26{txt}{col 49}Pseudo R2{col 67}= {res}    0.0301

{txt}{ralign 78:(Std. Err. adjusted for {res:28,044} clusters in FIRM_id)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}     PROFITS{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}ETR {c |}{col 14}{res}{space 2}-.0092418{col 26}{space 2} .0007246{col 37}{space 1}  -12.75{col 46}{space 3}0.000{col 54}{space 4} -.010662{col 67}{space 3}-.0078215
{txt}{space 6}ETRxTD {c |}{col 14}{res}{space 2}-.0027166{col 26}{space 2} .0009771{col 37}{space 1}   -2.78{col 46}{space 3}0.005{col 54}{space 4}-.0046317{col 67}{space 3}-.0008015
{txt}{space 5}lnSALES {c |}{col 14}{res}{space 2} .5829113{col 26}{space 2} .0145629{col 37}{space 1}   40.03{col 46}{space 3}0.000{col 54}{space 4} .5543686{col 67}{space 3}  .611454
{txt}{space 7}lnEMP {c |}{col 14}{res}{space 2} .0456964{col 26}{space 2} .0115985{col 37}{space 1}    3.94{col 46}{space 3}0.000{col 54}{space 4} .0229638{col 67}{space 3}  .068429
{txt}{space 7}lnGDP {c |}{col 14}{res}{space 2} .1479308{col 26}{space 2} .0247056{col 37}{space 1}    5.99{col 46}{space 3}0.000{col 54}{space 4} .0995088{col 67}{space 3} .1963528
{txt}{space 5}lnKLRAT {c |}{col 14}{res}{space 2} .0864753{col 26}{space 2}  .008019{col 37}{space 1}   10.78{col 46}{space 3}0.000{col 54}{space 4} .0707584{col 67}{space 3} .1021923
{txt}{space 5}lnSKILL {c |}{col 14}{res}{space 2} .0230008{col 26}{space 2} .0195926{col 37}{space 1}    1.17{col 46}{space 3}0.240{col 54}{space 4}-.0154001{col 67}{space 3} .0614016
{txt}{space 5}lnLABOR {c |}{col 14}{res}{space 2}-.0647049{col 26}{space 2}  .075565{col 37}{space 1}   -0.86{col 46}{space 3}0.392{col 54}{space 4}-.2128095{col 67}{space 3} .0833998
{txt}{space 6}lnMARK {c |}{col 14}{res}{space 2}  .151956{col 26}{space 2} .0375151{col 37}{space 1}    4.05{col 46}{space 3}0.000{col 54}{space 4} .0784277{col 67}{space 3} .2254842
{txt}{space 4}lnPOPDEN {c |}{col 14}{res}{space 2}-.0586229{col 26}{space 2} .0224904{col 37}{space 1}   -2.61{col 46}{space 3}0.009{col 54}{space 4}-.1027032{col 67}{space 3}-.0145425
{txt}{space 4}lnINFRAS {c |}{col 14}{res}{space 2} .0490997{col 26}{space 2}  .025668{col 37}{space 1}    1.91{col 46}{space 3}0.056{col 54}{space 4}-.0012086{col 67}{space 3} .0994079
{txt}{space 3}lnFINANCE {c |}{col 14}{res}{space 2}-.1714158{col 26}{space 2} .0318112{col 37}{space 1}   -5.39{col 46}{space 3}0.000{col 54}{space 4}-.2337646{col 67}{space 3} -.109067
{txt}{space 4}lnINVFOR {c |}{col 14}{res}{space 2}-.0506593{col 26}{space 2} .0131898{col 37}{space 1}   -3.84{col 46}{space 3}0.000{col 54}{space 4}-.0765109{col 67}{space 3}-.0248078
{txt}{space 7}y2006 {c |}{col 14}{res}{space 2}-.0199239{col 26}{space 2} .0149546{col 37}{space 1}   -1.33{col 46}{space 3}0.183{col 54}{space 4}-.0492343{col 67}{space 3} .0093865
{txt}{space 7}y2007 {c |}{col 14}{res}{space 2}-.0273431{col 26}{space 2} .0268804{col 37}{space 1}   -1.02{col 46}{space 3}0.309{col 54}{space 4}-.0800276{col 67}{space 3} .0253414
{txt}{space 7}y2008 {c |}{col 14}{res}{space 2}  .043575{col 26}{space 2} .0408331{col 37}{space 1}    1.07{col 46}{space 3}0.286{col 54}{space 4}-.0364564{col 67}{space 3} .1236064
{txt}{space 7}y2009 {c |}{col 14}{res}{space 2} .0540629{col 26}{space 2} .0449298{col 37}{space 1}    1.20{col 46}{space 3}0.229{col 54}{space 4}-.0339979{col 67}{space 3} .1421237
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .8374702{col 26}{space 2} .8643772{col 37}{space 1}    0.97{col 46}{space 3}0.333{col 54}{space 4} -.856678{col 67}{space 3} 2.531618
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}/lndelta {c |}{col 14}{res}{space 2} 10.19655{col 26}{space 2} .0582557{col 54}{space 4} 10.08237{col 67}{space 3} 10.31073
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
       delta {c |}{col 14}{res}{space 2} 26810.53{col 26}{space 2} 1561.867{col 54}{space 4} 23917.63{col 67}{space 3} 30053.34
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. est store component1
{txt}
{com}. estat ic

Akaike's information criterion and Bayesian information criterion

{txt}{hline 13}{c TT}{hline 63}
       Model {c |}        Obs  ll(null)  ll(model)      df         AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:{stata estimates replay component1:component1}}{col 14}{c |}{res}{col 16}    57,802{col 27}-603444.8{col 38}-585302.3{col 49}    19{col 58}  1170643{col 69}  1170813
{txt}{hline 13}{c BT}{hline 63}
{p 15 21 2}
Note: N=Obs used in calculating BIC; see {helpb bic_note:[R] BIC note}.
{p_end}

{com}. matrix comp1 = r(S)
{txt}
{com}. 
. 
. fmm 2 if insample == 1, vce(cluster FIRM_id)  : nbreg PROFITS ETR ETRxTD ///
>       lnSALES lnEMP lnGDP lnKLRAT lnSKILL lnLABOR lnMARK lnPOPDEN lnINFRAS ///
>           lnFINANCE lnINVFOR y2006-y2009, dispersion(constant)
{res}{txt}
Fitting class model:

Iteration 0:{space 3}(class) log likelihood = {res:-40065.293}  
Iteration 1:{space 3}(class) log likelihood = {res:-40065.293}  

Fitting outcome model:

Iteration 0:{space 3}(outcome) log likelihood = {res:-4.131e+08}  (not concave)
Iteration 1:{space 3}(outcome) log likelihood = {res:-721809.99}  (not concave)
Iteration 2:{space 3}(outcome) log likelihood = {res:-671535.52}  (not concave)
Iteration 3:{space 3}(outcome) log likelihood = {res:-608580.99}  (not concave)
Iteration 4:{space 3}(outcome) log likelihood = {res:-594278.23}  
Iteration 5:{space 3}(outcome) log likelihood = {res:-588421.92}  
Iteration 6:{space 3}(outcome) log likelihood = {res:-584209.55}  
Iteration 7:{space 3}(outcome) log likelihood = {res:-583891.96}  
Iteration 8:{space 3}(outcome) log likelihood = {res: -583891.8}  
Iteration 9:{space 3}(outcome) log likelihood = {res: -583891.8}  

Refining starting values:

Iteration 0:{space 3}(EM) log likelihood = {res:-616867.21}
Iteration 1:{space 3}(EM) log likelihood = {res:-607840.21}
Iteration 2:{space 3}(EM) log likelihood = {res:-599857.94}
Iteration 3:{space 3}(EM) log likelihood = {res:-594697.03}
Iteration 4:{space 3}(EM) log likelihood = {res: -591940.5}
Iteration 5:{space 3}(EM) log likelihood = {res:-590538.92}
Iteration 6:{space 3}(EM) log likelihood = {res:-589783.38}
Iteration 7:{space 3}(EM) log likelihood = {res:-589323.26}
Iteration 8:{space 3}(EM) log likelihood = {res:-589002.89}
Iteration 9:{space 3}(EM) log likelihood = {res:-588755.13}
Iteration 10:{space 2}(EM) log likelihood = {res: -588550.7}
Iteration 11:{space 2}(EM) log likelihood = {res:-588376.17}
Iteration 12:{space 2}(EM) log likelihood = {res:-588224.79}
Iteration 13:{space 2}(EM) log likelihood = {res: -588092.6}
Iteration 14:{space 2}(EM) log likelihood = {res:-587976.93}
Iteration 15:{space 2}(EM) log likelihood = {res:-587875.68}
Iteration 16:{space 2}(EM) log likelihood = {res:-587787.06}
Iteration 17:{space 2}(EM) log likelihood = {res:-587709.56}
Iteration 18:{space 2}(EM) log likelihood = {res:-587641.85}
Iteration 19:{space 2}(EM) log likelihood = {res:-587582.68}
Iteration 20:{space 2}(EM) log likelihood = {res:-587531.08}
{p}
Note: EM algorithm reached maximum iterations.
{p_end}

Fitting full model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-568578.86}  
Iteration 1:{space 3}log pseudolikelihood = {res:-568577.13}  
Iteration 2:{space 3}log pseudolikelihood = {res:-568577.13}  
{res}
{txt}Finite mixture model{col 49}Number of obs{col 67}= {res}    57,802
{txt}Log pseudolikelihood = {res}-568577.13

{txt}{ralign 78:(Std. Err. adjusted for {res:28,044} clusters in FIRM_id)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}1.Class     {col 14}{txt}{c |}  (base outcome)
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}2.Class      {txt}{c |}
{space 7}_cons {c |}{col 14}{res}{space 2}-1.335792{col 26}{space 2} .0688097{col 37}{space 1}  -19.41{col 46}{space 3}0.000{col 54}{space 4}-1.470657{col 67}{space 3}-1.200928
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Class{col 16}: {res}1
{txt}Response{col 16}: {res}PROFITS
{txt}Model{col 16}: {res}nbreg, dispersion(constant)

{txt}{ralign 78:(Std. Err. adjusted for {res:28,044} clusters in FIRM_id)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}PROFITS      {txt}{c |}
{space 9}ETR {c |}{col 14}{res}{space 2}-.0139211{col 26}{space 2} .0006198{col 37}{space 1}  -22.46{col 46}{space 3}0.000{col 54}{space 4} -.015136{col 67}{space 3}-.0127063
{txt}{space 6}ETRxTD {c |}{col 14}{res}{space 2}-.0016905{col 26}{space 2}  .000974{col 37}{space 1}   -1.74{col 46}{space 3}0.083{col 54}{space 4}-.0035995{col 67}{space 3} .0002185
{txt}{space 5}lnSALES {c |}{col 14}{res}{space 2} .7135152{col 26}{space 2} .0131537{col 37}{space 1}   54.24{col 46}{space 3}0.000{col 54}{space 4} .6877345{col 67}{space 3} .7392959
{txt}{space 7}lnEMP {c |}{col 14}{res}{space 2}-.0233663{col 26}{space 2} .0098745{col 37}{space 1}   -2.37{col 46}{space 3}0.018{col 54}{space 4}-.0427199{col 67}{space 3}-.0040126
{txt}{space 7}lnGDP {c |}{col 14}{res}{space 2} .1685763{col 26}{space 2}  .019719{col 37}{space 1}    8.55{col 46}{space 3}0.000{col 54}{space 4} .1299277{col 67}{space 3} .2072248
{txt}{space 5}lnKLRAT {c |}{col 14}{res}{space 2} .0954269{col 26}{space 2} .0064228{col 37}{space 1}   14.86{col 46}{space 3}0.000{col 54}{space 4} .0828385{col 67}{space 3} .1080153
{txt}{space 5}lnSKILL {c |}{col 14}{res}{space 2} .0583305{col 26}{space 2} .0172784{col 37}{space 1}    3.38{col 46}{space 3}0.001{col 54}{space 4} .0244655{col 67}{space 3} .0921955
{txt}{space 5}lnLABOR {c |}{col 14}{res}{space 2}-.2241636{col 26}{space 2} .0576733{col 37}{space 1}   -3.89{col 46}{space 3}0.000{col 54}{space 4}-.3372013{col 67}{space 3} -.111126
{txt}{space 6}lnMARK {c |}{col 14}{res}{space 2} .2293275{col 26}{space 2} .0306292{col 37}{space 1}    7.49{col 46}{space 3}0.000{col 54}{space 4} .1692954{col 67}{space 3} .2893595
{txt}{space 4}lnPOPDEN {c |}{col 14}{res}{space 2}-.0147185{col 26}{space 2} .0198986{col 37}{space 1}   -0.74{col 46}{space 3}0.459{col 54}{space 4} -.053719{col 67}{space 3} .0242821
{txt}{space 4}lnINFRAS {c |}{col 14}{res}{space 2} .0191209{col 26}{space 2} .0234204{col 37}{space 1}    0.82{col 46}{space 3}0.414{col 54}{space 4}-.0267822{col 67}{space 3}  .065024
{txt}{space 3}lnFINANCE {c |}{col 14}{res}{space 2}-.2076464{col 26}{space 2} .0298101{col 37}{space 1}   -6.97{col 46}{space 3}0.000{col 54}{space 4}-.2660732{col 67}{space 3}-.1492196
{txt}{space 4}lnINVFOR {c |}{col 14}{res}{space 2}-.0169108{col 26}{space 2} .0122415{col 37}{space 1}   -1.38{col 46}{space 3}0.167{col 54}{space 4}-.0409037{col 67}{space 3} .0070821
{txt}{space 7}y2006 {c |}{col 14}{res}{space 2}-.0132429{col 26}{space 2}  .016329{col 37}{space 1}   -0.81{col 46}{space 3}0.417{col 54}{space 4}-.0452472{col 67}{space 3} .0187613
{txt}{space 7}y2007 {c |}{col 14}{res}{space 2}-.0116593{col 26}{space 2}   .02244{col 37}{space 1}   -0.52{col 46}{space 3}0.603{col 54}{space 4}-.0556409{col 67}{space 3} .0323222
{txt}{space 7}y2008 {c |}{col 14}{res}{space 2} .0376219{col 26}{space 2} .0327659{col 37}{space 1}    1.15{col 46}{space 3}0.251{col 54}{space 4}-.0265981{col 67}{space 3} .1018419
{txt}{space 7}y2009 {c |}{col 14}{res}{space 2} .0709202{col 26}{space 2} .0363745{col 37}{space 1}    1.95{col 46}{space 3}0.051{col 54}{space 4}-.0003725{col 67}{space 3} .1422128
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-.5125377{col 26}{space 2} .6750298{col 37}{space 1}   -0.76{col 46}{space 3}0.448{col 54}{space 4}-1.835572{col 67}{space 3} .8104963
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}/PROFITS     {txt}{c |}
{space 5}lndelta {c |}{col 14}{res}{space 2} 8.159915{col 26}{space 2} .0434634{col 54}{space 4} 8.074728{col 67}{space 3} 8.245102
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Class{col 16}: {res}2
{txt}Response{col 16}: {res}PROFITS
{txt}Model{col 16}: {res}nbreg, dispersion(constant)

{txt}{ralign 78:(Std. Err. adjusted for {res:28,044} clusters in FIRM_id)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}PROFITS      {txt}{c |}
{space 9}ETR {c |}{col 14}{res}{space 2}-.0093657{col 26}{space 2} .0015838{col 37}{space 1}   -5.91{col 46}{space 3}0.000{col 54}{space 4}-.0124698{col 67}{space 3}-.0062616
{txt}{space 6}ETRxTD {c |}{col 14}{res}{space 2}-.0025999{col 26}{space 2}  .002149{col 37}{space 1}   -1.21{col 46}{space 3}0.226{col 54}{space 4}-.0068118{col 67}{space 3} .0016121
{txt}{space 5}lnSALES {c |}{col 14}{res}{space 2} .4758822{col 26}{space 2} .0223275{col 37}{space 1}   21.31{col 46}{space 3}0.000{col 54}{space 4}  .432121{col 67}{space 3} .5196433
{txt}{space 7}lnEMP {c |}{col 14}{res}{space 2} .0962158{col 26}{space 2} .0192253{col 37}{space 1}    5.00{col 46}{space 3}0.000{col 54}{space 4} .0585348{col 67}{space 3} .1338967
{txt}{space 7}lnGDP {c |}{col 14}{res}{space 2} .1358493{col 26}{space 2} .0443143{col 37}{space 1}    3.07{col 46}{space 3}0.002{col 54}{space 4} .0489949{col 67}{space 3} .2227036
{txt}{space 5}lnKLRAT {c |}{col 14}{res}{space 2} .0883188{col 26}{space 2} .0140171{col 37}{space 1}    6.30{col 46}{space 3}0.000{col 54}{space 4} .0608457{col 67}{space 3} .1157919
{txt}{space 5}lnSKILL {c |}{col 14}{res}{space 2} .0160825{col 26}{space 2}  .033336{col 37}{space 1}    0.48{col 46}{space 3}0.629{col 54}{space 4} -.049255{col 67}{space 3} .0814199
{txt}{space 5}lnLABOR {c |}{col 14}{res}{space 2} .0495236{col 26}{space 2} .1303282{col 37}{space 1}    0.38{col 46}{space 3}0.704{col 54}{space 4} -.205915{col 67}{space 3} .3049622
{txt}{space 6}lnMARK {c |}{col 14}{res}{space 2}  .116982{col 26}{space 2} .0641541{col 37}{space 1}    1.82{col 46}{space 3}0.068{col 54}{space 4}-.0087577{col 67}{space 3} .2427218
{txt}{space 4}lnPOPDEN {c |}{col 14}{res}{space 2}-.0654376{col 26}{space 2} .0361652{col 37}{space 1}   -1.81{col 46}{space 3}0.070{col 54}{space 4}-.1363202{col 67}{space 3}  .005445
{txt}{space 4}lnINFRAS {c |}{col 14}{res}{space 2} .0373999{col 26}{space 2} .0438738{col 37}{space 1}    0.85{col 46}{space 3}0.394{col 54}{space 4}-.0485911{col 67}{space 3} .1233909
{txt}{space 3}lnFINANCE {c |}{col 14}{res}{space 2}-.1249959{col 26}{space 2} .0553474{col 37}{space 1}   -2.26{col 46}{space 3}0.024{col 54}{space 4}-.2334748{col 67}{space 3}-.0165169
{txt}{space 4}lnINVFOR {c |}{col 14}{res}{space 2} -.083817{col 26}{space 2} .0235683{col 37}{space 1}   -3.56{col 46}{space 3}0.000{col 54}{space 4}-.1300101{col 67}{space 3} -.037624
{txt}{space 7}y2006 {c |}{col 14}{res}{space 2}-.0125263{col 26}{space 2} .0320982{col 37}{space 1}   -0.39{col 46}{space 3}0.696{col 54}{space 4}-.0754376{col 67}{space 3}  .050385
{txt}{space 7}y2007 {c |}{col 14}{res}{space 2}-.0182927{col 26}{space 2} .0484957{col 37}{space 1}   -0.38{col 46}{space 3}0.706{col 54}{space 4}-.1133425{col 67}{space 3} .0767572
{txt}{space 7}y2008 {c |}{col 14}{res}{space 2} .0383905{col 26}{space 2} .0738326{col 37}{space 1}    0.52{col 46}{space 3}0.603{col 54}{space 4}-.1063187{col 67}{space 3} .1830996
{txt}{space 7}y2009 {c |}{col 14}{res}{space 2} .0572541{col 26}{space 2} .0802166{col 37}{space 1}    0.71{col 46}{space 3}0.475{col 54}{space 4}-.0999675{col 67}{space 3} .2144757
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 2.067425{col 26}{space 2}  1.41615{col 37}{space 1}    1.46{col 46}{space 3}0.144{col 54}{space 4} -.708178{col 67}{space 3} 4.843029
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}/PROFITS     {txt}{c |}
{space 5}lndelta {c |}{col 14}{res}{space 2} 11.56554{col 26}{space 2} .1084777{col 54}{space 4} 11.35293{col 67}{space 3} 11.77816
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. test _b[PROFITS:2.Class#c.ETRxTD] - _b[PROFITS:1.Class#c.ETRxTD]==0

{p 0 7}{space 1}{text:( 1)}{space 1}{space 1}{res}- [PROFITS]1bn.Class#c.ETRxTD + [PROFITS]2.Class#c.ETRxTD = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.12
{txt}{col 10}Prob > chi2 =  {res}  0.7318
{txt}
{com}. est store component2
{txt}
{com}. estat ic

Akaike's information criterion and Bayesian information criterion

{txt}{hline 13}{c TT}{hline 63}
       Model {c |}        Obs  ll(null)  ll(model)      df         AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:{stata estimates replay component2:component2}}{col 14}{c |}{res}{col 16}    57,802{col 27}        .{col 38}-568577.1{col 49}    39{col 58}  1137232{col 69}  1137582
{txt}{hline 13}{c BT}{hline 63}
{p 15 21 2}
Note: N=Obs used in calculating BIC; see {helpb bic_note:[R] BIC note}.
{p_end}

{com}. matrix comp2 = r(S)
{txt}
{com}. 
. // Evidence that the 2 component model is better that 1 component model
. matrix list comp1 
{res}
{txt}comp1[1,6]
                     N         ll0          ll          df         AIC         BIC
component1 {res}      57802  -603444.81  -585302.26          19   1170642.5   1170812.8
{reset}
{com}. matrix list comp2
{res}
{txt}comp2[1,6]
                     N         ll0          ll          df         AIC         BIC
component2 {res}      57802           .  -568577.13          39   1137232.3   1137581.9
{reset}
{com}. lrtest component1 component2, force

{txt}Likelihood-ratio test{col 55}LR chi2({res}20{txt}){col 67}={res}  33450.25
{txt}(Assumption: {res}{stata est replay component1:component1}{txt} nested in {res}{stata est replay component2:component2}{txt}){col 55}Prob > chi2 = {res}   0.0000
{txt}
{com}. 
. etime
{res}Elapsed time is 1 minutes 17 seconds 
{txt}
{com}. 
. log close
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}\\file\UsersW$\wrr15\Home\My Documents\My Files\FIGO'S PAPER\REVISION FOR ECONOMICS E-JOURNAL\Revision (20180407)\FILES FROM FIGO (20180420)\MainResults.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res}20 Apr 2018, 09:11:27
{txt}{.-}
{smcl}
{txt}{sf}{ul off}